测绘通报 ›› 2022, Vol. 0 ›› Issue (6): 49-54142.doi: 10.13474/j.cnki.11-2246.2022.0170.

• 学术研究 • 上一篇    下一篇

一种复合型校正植被信息的方法

李茂林1, 闫庆武2, 仲晓雅1   

  1. 1. 中国矿业大学环境与测绘学院, 江苏 徐州 221116;
    2. 中国矿业大学公共管理学院, 江苏 徐州 221116
  • 收稿日期:2021-11-09 修回日期:2022-05-02 发布日期:2022-06-30
  • 作者简介:李茂林(1996-),男,硕士,主要从事GIS应用方面的研究。E-mail:LeeMaolin@cumt.edu.cn通信简介:闫庆武。E-mail:yanqingwu@cumt.edu.cn
  • 基金资助:
    内蒙古自治区科技计划(2060399—273);国家自然科学基金(51874306)

A compound method for correcting vegetation information

LI Maolin1, YAN Qingwu2, ZHONG Xiaoya1   

  1. 1. College of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China;
    2. School of Public Policy and Management, China University of Mining and Technology, Xuzhou 221116, China
  • Received:2021-11-09 Revised:2022-05-02 Published:2022-06-30

摘要: 遥感技术能快速获取大范围的植被信息,但却存在植被信息混分等问题。基于地物光谱差异特征,本文采用复合植被指数的形式提出了一种校正植被信息的方法。结果表明:在增强植被信息方面,该方法弥补了NDVIRad过饱和的缺点,使得高覆盖植被的信息值在0.7以上;在抑制非植被方面,该方法将植被和非植被进行了分离,使得大部分非植被的信息值在0以下;此外,在“抗地形”方面,该方法引入了“抗地形”因子(δ/Red),一定程度上削减了地形对植被提取带来的影响。

关键词: 植被, 光谱分析, 地形, 植被指数, 遥感影像

Abstract: Remote sensing technology can quickly obtain a large range of vegetation information. However, there exist some problems such as mixed classification of vegetation information. Therefore, a compound method for correcting vegetation information is established in the form of composite wavebands on the basis of spectral difference characteristics of ground objects. It is found that in terms of enhancing vegetation information, the method makes the information of high-cover vegetation information above 0.7, and alleviates the phenomenon of NDVIrad over-saturation in high-cover vegetation. In terms of restraining non-vegetation features, the method separate vegetation from non-vegetation. making the information of most non-vegetation features information below zero. Additionally, in terms of anti-terrain, the method introduces δ/Red factor, reducing the impact of terrain on vegetation extraction to some extent.

Key words: vegetation, spectrum analysis, topography, vegetation index, remote sensing image

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